Agriculture provides the most basic needs of humankind. New agricultural techniques should be able to meet future demands while maintaining or reducing the environmental footprint of agriculture.

Emerging technologies such as AI and EO could be utilized to make informed management decisions aimed to increase crop productions. Precision agriculture (PA) entails the applications of such technologies to optimise agricultural inputs, in order to increase production and reduce input losses.

The use of remote sensing technologies for PA has increased rapidly during the past few decades. The unprecedented availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing in many PA applications including crop monitoring, irrigation management, nutrient application, disease and pest management, and yield protection.

The EFTAS CropAnalyzer application is used toannotate field photos of crops automatically to the growing crop type. It couldthus support (citizen) field-based data collection for training/validation ofcrop type products. The Network is trained on 80.000 field photos from2012-2019 collected from ~40.000 locations. It provides a model accuracy of90%.

Featured Educators

• Oliver Buck
• Susanne Kocjan, EFTAS

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